Nutrient and dissolved inorganic carbon variability in the North Pacific
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A compilation of surface water nutrient (phosphate, nitrate, and silicate) and partial pressure of CO 2 ( p CO 2 ) observations from 1961 to 2016 reveals seasonal and interannual variability in the North Pacific. Nutrients and calculated dissolved inorganic carbon (DIC) reach maximum concentrations in March and minimum in August. Nutrient and DIC variability is in-phase (anti-phase) with changes in the mixed layer depth (sea surface temperature) north of 30 °N, and it is anti-phase (in-phase) with changes in Chl-a north of 40 °N (in 30 °N–40 °N). Seasonal drawdown of nutrients and DIC is larger toward the northwest and shows a local maximum in the boundary region between the subarctic and subtropics. Stoichiometric ratios of seasonal drawdown show that, compared to nitrate, silicate drawdown is large in the northwestern subarctic including the Bering and Okhotsk seas, and drawdown of carbon is larger toward the south. Net community production in mixed layer from March to July is estimated to be more than 6 gC/m 2 /mo in the boundary region between the subarctic and subtropics, the western subarctic, the Gulf of Alaska, and the Bering Sea. Nutrient and DIC concentrations vary with the Pacific Decadal Oscillation and the North Pacific Gyre Oscillation which cause changes in horizontal advection and vertical mixing. The DIC trend is positive in all analysis area and large in the western subtropics (> 1.0 μmol/l/yr). Averaged over the analysis area, it is increasing by 0.77 ± 0.03 μmol/l/yr (0.75 ± 0.02 μmol/kg/yr).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it